Mayo Clinic's AI Tool 'StateViewer' Revolutionizes Dementia Diagnosis with 88% Accuracy

New AI tool helps clinicians identify brain activity patterns linked to nine types of dementia

Mayo ClinicJun 30 2025 Mayo Clinic researchers have developed a new artificial intelligence (AI) tool that helps clinicians identify brain activity patterns linked to nine types of dementia, including Alzheimer's disease, using a single, widely available scan - a transformative advance in early, accurate diagnosis. The tool, StateViewer, helped researchers identify the dementia type in 88% of cases, according to research published online on June 27, 2025, in Neurology, the medical journal of the American Academy of Neurology. It also enabled clinicians to interpret brain scans nearly twice as fast and with up to three times greater accuracy than standard workflows. Researchers trained and tested the AI on more than 3,600 scans, including images from patients with dementia and people without cognitive impairment. This innovation addresses a core challenge in dementia care: identifying the disease early and precisely, even when multiple conditions are present. As new treatments emerge, timely diagnosis helps match patients with the most appropriate care when it can have the greatest impact. The tool could bring advanced diagnostic support to clinics that lack neurology expertise. The rising toll of dementia Dementia affects more than 55 million people worldwide, with nearly 10 million new cases each year. Alzheimer's disease, the most common form, is now the fifth-leading cause of death globally. Diagnosing dementia typically requires cognitive tests, blood draws, imaging, clinical interviews and specialist referrals. Even with extensive testing, distinguishing conditions such as Alzheimer's, Lewy body dementia and frontotemporal dementia remains challenging, including for highly experienced specialists. StateViewer was developed under the direction of David Jones, M.D., a Mayo Clinic neurologist and director of the Mayo Clinic Neurology Artificial Intelligence Program. Every patient who walks into my clinic carries a unique story shaped by the brain's complexity. That complexity drew me to neurology and continues to drive my commitment to clearer answers. StateViewer reflects that commitment - a step toward earlier understanding, more precise treatment and, one day, changing the course of these diseases." David Jones, M.D., Mayo Clinic neurologist To bring that vision to life, Dr. Jones worked alongside Leland Barnard, Ph.D., a data scientist who leads the AI engineering behind StateViewer. "As we were designing StateViewer, we never lost sight of the fact that behind every data point and brain scan was a person facing a difficult diagnosis and urgent questions," Dr. Barnard says. "Seeing how this tool could assist physicians with real-time, precise insights and guidance highlights the potential of machine learning for clinical medicine." Turning brain patterns into clinical insight The tool analyzes a fluorodeoxyglucose positron emission tomography (FDG-PET) scan, which shows how the brain uses glucose for energy. It then compares the scan to a large database of scans from people with confirmed dementia diagnoses and identifies patterns that match specific types, or combinations, of dementia. Alzheimer's typically affects memory and processing regions, Lewy body dementia involves areas tied to attention and movement, and frontotemporal dementia alters regions responsible for language and behavior. StateViewer displays these patterns through color-coded brain maps that highlight key areas of brain activity, giving all clinicians, even those without neurology training, a visual explanation of what the AI sees and how it supports the diagnosis. Mayo Clinic researchers plan to expand the tool's use and will continue evaluating its performance in a variety of clinical settings. Mayo Clinic Journal reference: Barnard, L., et al. (2025). An FDG-PET-Based Machine Learning Framework to Support Neurologic Decision-Making in Alzheimer Disease and Related Disorders. Neurology. doi.org/10.1212/wnl.0000000000213831.

New AI tool helps clinicians identify brain activity patterns linked to nine types of dementia

Mayo ClinicJul 3 2025 Mayo Clinic researchers have developed a new artificial intelligence (AI) tool that helps clinicians identify brain activity patterns linked to nine types of dementia, including Alzheimer's disease, using a single, widely available scan - a transformative advance in early, accurate diagnosis. The tool, StateViewer, helped researchers identify the dementia type in 88% of cases, according to research published online on June 27, 2025, in Neurology, the medical journal of the American Academy of Neurology. It also enabled clinicians to interpret brain scans nearly twice as fast and with up to three times greater accuracy than standard workflows. Researchers trained and tested the AI on more than 3,600 scans, including images from patients with dementia and people without cognitive impairment. This innovation addresses a core challenge in dementia care: identifying the disease early and precisely, even when multiple conditions are present. As new treatments emerge, timely diagnosis helps match patients with the most appropriate care when it can have the greatest impact. The tool could bring advanced diagnostic support to clinics that lack neurology expertise. The rising toll of dementia Dementia affects more than 55 million people worldwide, with nearly 10 million new cases each year. Alzheimer's disease, the most common form, is now the fifth-leading cause of death globally. Diagnosing dementia typically requires cognitive tests, blood draws, imaging, clinical interviews and specialist referrals. Even with extensive testing, distinguishing conditions such as Alzheimer's, Lewy body dementia and frontotemporal dementia remains challenging, including for highly experienced specialists. StateViewer was developed under the direction of David Jones, M.D., a Mayo Clinic neurologist and director of the Mayo Clinic Neurology Artificial Intelligence Program. Every patient who walks into my clinic carries a unique story shaped by the brain's complexity. That complexity drew me to neurology and continues to drive my commitment to clearer answers. StateViewer reflects that commitment - a step toward earlier understanding, more precise treatment and, one day, changing the course of these diseases." Dr. David Jones, M.D., Mayo Clinic neurologist To bring that vision to life, Dr. Jones worked alongside Leland Barnard, Ph.D., a data scientist who leads the AI engineering behind StateViewer. "As we were designing StateViewer, we never lost sight of the fact that behind every data point and brain scan was a person facing a difficult diagnosis and urgent questions," Dr. Barnard says. "Seeing how this tool could assist physicians with real-time, precise insights and guidance highlights the potential of machine learning for clinical medicine." Turning brain patterns into clinical insight The tool analyzes a fluorodeoxyglucose positron emission tomography (FDG-PET) scan, which shows how the brain uses glucose for energy. It then compares the scan to a large database of scans from people with confirmed dementia diagnoses and identifies patterns that match specific types, or combinations, of dementia. Alzheimer's typically affects memory and processing regions, Lewy body dementia involves areas tied to attention and movement, and frontotemporal dementia alters regions responsible for language and behavior. StateViewer displays these patterns through color-coded brain maps that highlight key areas of brain activity, giving all clinicians, even those without neurology training, a visual explanation of what the AI sees and how it supports the diagnosis. Mayo Clinic researchers plan to expand the tool's use and will continue evaluating its performance in a variety of clinical settings. Mayo Clinic Journal reference: Barnard, L., et al. (2025). An FDG-PET-Based Machine Learning Framework to Support Neurologic Decision-Making in Alzheimer Disease and Related Disorders. Neurology. doi.org/10.1212/wnl.0000000000213831.

AI tool detects 9 types of dementia from a single brain scan

Mayo Clinic researchers have developed a new artificial intelligence (AI) tool that helps clinicians identify brain activity patterns linked to nine types of dementia, including Alzheimer's disease, using a single, widely available scan -- a transformative advance in early, accurate diagnosis. The tool, StateViewer, helped researchers identify the dementia type in 88% of cases, according to research published online on June 27, 2025, in Neurology, the medical journal of the American Academy of Neurology. It also enabled clinicians to interpret brain scans nearly twice as fast and with up to three times greater accuracy than standard workflows. Researchers trained and tested the AI on more than 3,600 scans, including images from patients with dementia and people without cognitive impairment. This innovation addresses a core challenge in dementia care: identifying the disease early and precisely, even when multiple conditions are present. As new treatments emerge, timely diagnosis helps match patients with the most appropriate care when it can have the greatest impact. The tool could bring advanced diagnostic support to clinics that lack neurology expertise. The rising toll of dementia Dementia affects more than 55 million people worldwide, with nearly 10 million new cases each year. Alzheimer's disease, the most common form, is now the fifth-leading cause of death globally. Diagnosing dementia typically requires cognitive tests, blood draws, imaging, clinical interviews and specialist referrals. Even with extensive testing, distinguishing conditions such as Alzheimer's, Lewy body dementia and frontotemporal dementia remains challenging, including for highly experienced specialists. StateViewer was developed under the direction of David Jones, M.D., a Mayo Clinic neurologist and director of the Mayo Clinic Neurology Artificial Intelligence Program. "Every patient who walks into my clinic carries a unique story shaped by the brain's complexity," Dr. Jones says. "That complexity drew me to neurology and continues to drive my commitment to clearer answers. StateViewer reflects that commitment -- a step toward earlier understanding, more precise treatment and, one day, changing the course of these diseases." To bring that vision to life, Dr. Jones worked alongside Leland Barnard, Ph.D., a data scientist who leads the AI engineering behind StateViewer. "As we were designing StateViewer, we never lost sight of the fact that behind every data point and brain scan was a person facing a difficult diagnosis and urgent questions," Dr. Barnard says. "Seeing how this tool could assist physicians with real-time, precise insights and guidance highlights the potential of machine learning for clinical medicine." Turning brain patterns into clinical insight The tool analyzes a fluorodeoxyglucose positron emission tomography (FDG-PET) scan, which shows how the brain uses glucose for energy. It then compares the scan to a large database of scans from people with confirmed dementia diagnoses and identifies patterns that match specific types, or combinations, of dementia. Alzheimer's typically affects memory and processing regions, Lewy body dementia involves areas tied to attention and movement, and frontotemporal dementia alters regions responsible for language and behavior. StateViewer displays these patterns through color-coded brain maps that highlight key areas of brain activity, giving all clinicians, even those without neurology training, a visual explanation of what the AI sees and how it supports the diagnosis. Mayo Clinic researchers plan to expand the tool's use and will continue evaluating its performance in a variety of clinical settings.

New AI identifies nine types of dementia with 88% diagnostic accuracy

The study published recently reports that StateViewer identified the correct dementia type in 88% of cases. It also doubled interpretation speed and tripled diagnostic accuracy compared to standard workflows. The AI was trained and tested on over 3,600 brain scans, covering patients with and without cognitive impairment. As new treatments for dementia become available, timely and precise diagnosis is essential. StateViewer offers a scalable solution that could bring expert-level diagnostic support to clinics lacking specialized neurology care. StateViewer analyzes a fluorodeoxyglucose positron emission tomography (FDG-PET) scan, which shows how the brain uses glucose, a key indicator of brain activity. It then compares the scan against a vast database of scans from patients with confirmed dementia diagnoses. Using machine learning, the tool detects distinct brain activity patterns tied to specific dementia types. Different forms of dementia affect different brain regions. Alzheimer's targets memory and processing areas. Lewy body dementia impacts attention and motor-related zones. Frontotemporal dementia affects language and behavior-related regions.

Mayo Clinic's AI Tool Identifies 9 Dementia Types, Including Alzheimer's, with One Scan | Newswise

Newswise -- ROCHESTER, Minn. -- Mayo Clinic researchers have developed a new artificial intelligence (AI) tool that helps clinicians identify brain activity patterns linked to nine types of dementia, including Alzheimer's disease, using a single, widely available scan -- a transformative advance in early, accurate diagnosis. The tool, StateViewer, helped researchers identify the dementia type in 88% of cases, according to research published online on June 27, 2025, in Neurology, the medical journal of the American Academy of Neurology. It also enabled clinicians to interpret brain scans nearly twice as fast and with up to three times greater accuracy than standard workflows. Researchers trained and tested the AI on more than 3,600 scans, including images from patients with dementia and people without cognitive impairment. This innovation addresses a core challenge in dementia care: identifying the disease early and precisely, even when multiple conditions are present. As new treatments emerge, timely diagnosis helps match patients with the most appropriate care when it can have the greatest impact. The tool could bring advanced diagnostic support to clinics that lack neurology expertise. Dementia affects more than 55 million people worldwide, with nearly 10 million new cases each year. Alzheimer's disease, the most common form, is now the fifth-leading cause of death globally. Diagnosing dementia typically requires cognitive tests, blood draws, imaging, clinical interviews and specialist referrals. Even with extensive testing, distinguishing conditions such as Alzheimer's, Lewy body dementia and frontotemporal dementia remains challenging, including for highly experienced specialists. StateViewer was developed under the direction of David Jones, M.D., a Mayo Clinic neurologist and director of the Mayo Clinic Neurology Artificial Intelligence Program. "Every patient who walks into my clinic carries a unique story shaped by the brain's complexity," Dr. Jones says. "That complexity drew me to neurology and continues to drive my commitment to clearer answers. StateViewer reflects that commitment -- a step toward earlier understanding, more precise treatment and, one day, changing the course of these diseases." To bring that vision to life, Dr. Jones worked alongside Leland Barnard, Ph.D., a data scientist who leads the AI engineering behind StateViewer. "As we were designing StateViewer, we never lost sight of the fact that behind every data point and brain scan was a person facing a difficult diagnosis and urgent questions," Dr. Barnard says. "Seeing how this tool could assist physicians with real-time, precise insights and guidance highlights the potential of machine learning for clinical medicine." The tool analyzes a fluorodeoxyglucose positron emission tomography (FDG-PET) scan, which shows how the brain uses glucose for energy. It then compares the scan to a large database of scans from people with confirmed dementia diagnoses and identifies patterns that match specific types, or combinations, of dementia. Alzheimer's typically affects memory and processing regions, Lewy body dementia involves areas tied to attention and movement, and frontotemporal dementia alters regions responsible for language and behavior. StateViewer displays these patterns through color-coded brain maps that highlight key areas of brain activity, giving all clinicians, even those without neurology training, a visual explanation of what the AI sees and how it supports the diagnosis. Mayo Clinic researchers plan to expand the tool's use and will continue evaluating its performance in a variety of clinical settings. About Mayo Clinic Mayo Clinic is a nonprofit organization committed to innovation in clinical practice, education and research, and providing compassion, expertise and answers to everyone who needs healing. Visit the Mayo Clinic News Network for additional Mayo Clinic news.

AI tool identifies 9 dementia types, including Alzheimer's, with one scan

ROCHESTER, Minn. -- Mayo Clinic researchers have developed a new artificial intelligence tool that helps clinicians identify brain activity patterns linked to nine types of dementia, including Alzheimer's disease, using a single, widely available scan -- a transformative advance in early, accurate diagnosis. The tool, StateViewer, helped researchers identify the dementia type in 88% of cases, according to research published online on June 27, 2025, in Neurology, the medical journal of the American Academy of Neurology. It also enabled clinicians to interpret brain scans nearly twice as fast and with up to three times greater accuracy than standard workflows. Researchers trained and tested the AI on more than 3,600 scans, including images from patients with dementia and people without cognitive impairment. This innovation addresses a core challenge in dementia care: identifying the disease early and precisely, even when multiple conditions are present. As new treatments emerge, timely diagnosis helps match patients with the most appropriate care when it can have the greatest impact. The tool could bring advanced diagnostic support to clinics that lack neurology expertise. The rising toll of dementia Dementia affects more than 55 million people worldwide, with nearly 10 million new cases each year. Alzheimer's disease, the most common form, is now the fifth-leading cause of death globally. Diagnosing dementia typically requires cognitive tests, blood draws, imaging, clinical interviews and specialist referrals. Even with extensive testing, distinguishing conditions such as Alzheimer's, Lewy body dementia and frontotemporal dementia remains challenging, including for highly experienced specialists. StateViewer was developed under the direction of Dr. David Jones, a Mayo Clinic neurologist and director of the Mayo Clinic Neurology Artificial Intelligence Program. "Every patient who walks into my clinic carries a unique story shaped by the brain's complexity," Jones says. "That complexity drew me to neurology and continues to drive my commitment to clearer answers. StateViewer reflects that commitment -- a step toward earlier understanding, more precise treatment and, one day, changing the course of these diseases." To bring that vision to life, Jones worked alongside Leland Barnard, a data scientist who leads the AI engineering behind StateViewer. "As we were designing StateViewer, we never lost sight of the fact that behind every data point and brain scan was a person facing a difficult diagnosis and urgent questions," Barnard says. "Seeing how this tool could assist physicians with real-time, precise insights and guidance highlights the potential of machine learning for clinical medicine." Turning brain patterns into clinical insight The tool analyzes a fluorodeoxyglucose positron emission tomography (FDG-PET) scan, which shows how the brain uses glucose for energy. It then compares the scan to a large database of scans from people with confirmed dementia diagnoses and identifies patterns that match specific types, or combinations, of dementia. Alzheimer's typically affects memory and processing regions, Lewy body dementia involves areas tied to attention and movement, and frontotemporal dementia alters regions responsible for language and behavior. StateViewer displays these patterns through color-coded brain maps that highlight key areas of brain activity, giving all clinicians, even those without neurology training, a visual explanation of what the AI sees and how it supports the diagnosis. Mayo Clinic researchers plan to expand the tool's use and will continue evaluating its performance in a variety of clinical settings.

AI Can Help Determine A Person's Specific Form Of Dementia

By Dennis Thompson HealthDay ReporterTUESDAY, July 1, 2025 (HealthDay News) -- A new AI tool can help doctors hone in on a patient's particular type of dementia, including Alzheimer's disease, a new study says. The AI tool, StateViewer, helped researchers identify a person's dementia type in 88% of cases, according to results newly published in the journal Neurology. The tool could help doctors identify dementia early and precisely, even when patients had many medical conditions that could be contributing to their cognitive problems, researchers said. "Every patient who walks into my clinic carries a unique story shaped by the brain's complexity," senior researcher Dr. David Jones, director of the Mayo Clinic Neurology Artificial Intelligence Program, said in a news release. "That complexity drew me to neurology and continues to drive my commitment to clearer answers." StateViewer reflects that commitment, he said, describing it as "a step toward earlier understanding, more precise treatment and, one day, changing the course of these diseases." Researchers trained and tested the AI on more than 3,600 brain imaging exams called fluorodeoxyglucose positron emission tomography (FDG-PET) scans, which show how the brain uses glucose for energy. The AI compares a person's brain images against a large database of scans from people with confirmed dementia diagnoses. It then identifies brain patterns that match specific types or combinations of dementia. For example, Alzheimer's typically affects memory and processing regions, researchers said. On the other hand, Lewy body dementia involves areas associated with attention and movement, and frontotemporal dementia alters regions responsible for language and behavior. Overall, the AI can sort through brain patterns associated with nine different types of dementia, researchers said. Color-coded brain maps highlight key areas of brain activity, giving doctors a visual explanation of what the AI sees and why it has given a particular diagnosis. "As we were designing StateViewer, we never lost sight of the fact that behind every data point and brain scan was a person facing a difficult diagnosis and urgent questions," lead researcher Leland Barnard, a data scientist with the Mayo Clinic, said in a news release. "Seeing how this tool could assist physicians with real-time, precise insights and guidance highlights the potential of machine learning for clinical medicine," he added. Mayo Clinic researchers plan to expand the tool's use and test its performance in a variety of clinical settings.